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ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
15 years 8 months ago
Spectral Regression: A Unified Approach for Sparse Subspace Learning
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
Deng Cai, Xiaofei He, Jiawei Han
TKDE
2002
124views more  TKDE 2002»
15 years 3 months ago
Clustering for Approximate Similarity Search in High-Dimensional Spaces
In this paper we present a clustering and indexing paradigm called Clindex for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where on...
Chen Li, Edward Y. Chang, Hector Garcia-Molina, Gi...
HAIS
2009
Springer
15 years 9 months ago
Unsupervised Feature Selection in High Dimensional Spaces and Uncertainty
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
José Ramón Villar, María del ...
NIPS
2007
15 years 5 months ago
Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data
Content-based image suggestion (CBIS) targets the recommendation of products based on user preferences on the visual content of images. In this paper, we motivate both feature sel...
Sabri Boutemedjet, Djemel Ziou, Nizar Bouguila
TKDE
2011
332views more  TKDE 2011»
14 years 11 months ago
Adaptive Cluster Distance Bounding for High-Dimensional Indexing
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
Sharadh Ramaswamy, Kenneth Rose